Field of the Invention
The present invention relates to a computed tomography (CT) image reconstruction methods, particularly referring to a system through a two-dimensional matrix for projection, comparison, back-projection and corrections to reduce the amount of computational and storage space.
Brief Discussion of the Related Art
Currently, CT image reconstruction system uses matrix in the reconstruction. It has been widely used in general iterative reconstruction method. However, with advanced technology in computer and image acquisition, the higher resolution the imaging detector, the larger information obtained, which requires a larger computing and storage resources. Although some instrument company may use connected multiple imaging workstations in series to achieve the operational purpose, technically, it still needs a large computing memory storage capacity for amount of these image data.
Please refer to U.S. Pat. No. 6,850,585 B2 and No. US20120098832, which disclose a multi-angle three-dimensional image reconstruction method using two-dimensional imaging. A detector system scans an object and causes at least one ray passing through the object, then uses the measured value for image reconstruction. The image reconstruction method comprises the following steps: first, use a plurality of voxels comprising a value of the three-dimensional image for the observed object to establish a reconstruction space. Then, project along the direction of the rays and compare the measured value for obtaining a correction value. Next, according to the correction value and each three-dimensional voxel value along the same tracing line but inversed, proceed back-projection. Finally, according to the correction value and the value of each three-dimensional voxel with respect to their corresponding relationship, obtain the modified correction value and update value after replacing the original value. Depending on users' needs, repeat several times iteratively for imaging reconstruction. The described technique above is based on iteration of each image for three-dimensional imaging, which has higher computational complexity.